I know very little about Bitcoin, and I’m almost too afraid too dive into the rabbit hole, but I did enjoy Scott Smith’s Bitcoin is just the poster currency for a growing movement of alternative tender. Instead of the usual discussions around its mechanics, Scott focuses on the reasons for the rise in alternative currencies in general, linking it to globalization and the rise of “formal-informal” markets. He also discusses why Bitcoin itself could be doomed already:

“Most of the action I see is around software development—people getting excited by local currency platforms, or virtual currencies,” wrote [Ken Banks, founder of a global initiative to promote economic self-sufficiency Means of Exchange]. “The problem here is that these are generally being run by techies, and we need to lead with the problem we’re trying to solve, not a cool technology. Most of the software being developed is unusable unless you have a degree in computing, or a server that costs about the same as a small car, and is hard to understand.”

You know what’s coming, right? Yep — this applies not just to Bitcoin, but to all product development. If you lead with technology instead of the problem you’re trying to solve, the resulting product will almost always be too complicated. It reminds me of a great line in the USA Today story Berlin airport fiasco an embarrassment for Germans:

Here, again, technology’s getting in the way: It’s so advanced that technicians can’t figure out what’s wrong with it.

So advanced that no one can figure out what’s wrong with it… Perhaps that’s the problem with Bitcoin, too?

Back in 2009, whenever an overly enthusiastic Foursquare user managed to capture the attention of an unsuspecting potential victim long enough to try to convince them to download the app, the conversation went something like this:

“It’s really cool. See? You ‘check in’ to the cafés and restaurants you visit.”

“Why?”

“Because if you check in enough times, you become the mayor of that place.”

“Why?”

“Because being the mayor is cool!”

“You keep using that word. I don’t think it means what you think it means. I think the word you’re looking for is lame.”

The discussion would usually dampen the Foursquare user’s enthusiasm a little bit, but only for a day or two. Then they’d be at it again, continuing their quest to spread the word about a service they don’t quite understand, but can’t help but be excited about.

Yesterday, Foursquare 6.0 was released for iOS and Android. And it continues a slow, steady move away from a focus on the ‘check-in’ to a way to discover great places to explore. If you squint and look at Foursquare just right, you’ll realize that they are becoming what Path wants to be: a social network for close friends and family.

The new Foursquare home screen continues the trend to reduce the hierarchy of the check-in action in favor of telling you what’s happening in your network, and what places you might like to visit (see left side of the screen below). A tap inside the (much more prominent) search bar brings up the interface to show recommended places to visit within a specified category (see right side of screen below).

See, what Foursquare realized a while ago is that their real power is not in the mayorships and badges that defined them in 2009. The real power — as usual — is the data. It’s knowing what people like and don’t like. It’s knowing where to find good coffee, what restaurants to avoid, and where you should go when you’re in a new city. And they have been shifting towards that vision with steadfast tenacity. Dan Frommer discussed this when Foursquare 5.0 was launched in June 2012:

So: Foursquare has been evolving to a company that no longer simply answers “where are my friends?” but instead “where should I go right now?” This is smart: Everyone’s gotta eat. That’s why Explore is rapidly becoming Foursquare’s most important feature. This has always been part of the plan, I think. But it’s certainly carrying more emphasis in this new version of the app than ever before.

With Foursquare 6.0, the company’s move towards a discovery engine powered by people you like and trust appears to be almost complete. That said, it’s clear that they’re not done (watch out, Path). I’m sure they are thinking of more ways to make the experience better. So even though there are some design irregularities in version 6.0, those will be ironed out through constant iteration while they’re moving towards a clear vision for the future. Like Anil Dash said at the beginning of 2012 in Foursquare: Today’s best-executing startup:

Foursquare’s removed features from the core app a few times, constantly changes the design of its flagship iOS application, and in general asserts its authority over the experience that users have within the Foursquare application. Yet, unlike every single other major social application, they don’t inspire mass user revolts or negative press every time they iterate. […] Part of this is the small, well-paced timing of iteration on the application where there are always small things changing in ways that aren’t wildly disruptive, but do enough to set a tone that users know to expect the furniture might get rearranged once in a while.

So, with all of that said… If you’ve tried Foursquare before and found it lame, I think you should give it another go. It’s not lame any more. Any service that can help you avoid bad coffee makes the world a better place, right? Foursquare is such a service, and so much more.

Oh, one more thing. Posting your Foursquare check-ins to Facebook and Twitter? Still lame.

There’s certainly a lot of hand-wringing going on about Facebook Home. And although there is some truth to articles like Facebook Home — My Personal Hell and Why Facebook Home bothers me: It destroys any notion of privacy, I feel like making this story’s headlines about how boring Facebook is and how it’s just another step towards evil corporations owning all our data is missing out on what’s really important about this announcement. The much more interesting question is this: How does Facebook Home impact identity?

Perhaps the best analysis I’ve seen about Facebook Home is a tweet written by Rebekah Cox back in January 2011:

The first company to fully execute on embedding your identity into your phone (making a truly first class experience) wins the next decade.

— R. Marie Cox (@artypapers) January 29, 2011

Rebekah expands on this in her post Mobile Identity, in which she concludes:

A mobile experience that truly represents your identity — in a way that both resembles and enhances an in-person conversation but still affords you control over how you portion out your attention and provides context — could tie the knot for the myriad communication channels available.

That certainly sounds like an accurate description of what Facebook is trying to do with this new product. Now add to that Dan Frommer’s analysis in Who’s Going To Buy The Facebook Phone?:

What about those millions of people who have bought Android phones who don’t really care that they’re Android phones, or even smartphones? […] My guess is that many — most? — of these people are Facebook users, and could easily see some utility in having Facebook features highlighted on their phones. And — bonus — Facebook’s software looks good. Much better than the junk that ships with typical low-end Android devices.

Put these two things together — identity and easy access — and Facebook’s strategy starts to become clear. For the majority of people life increasingly revolves around the Internet and their phones. This cartoon pretty much sums it up:

Image source: DOGHOUSE

It’s also clear that many people’s identities are getting tied up in Facebook. And Facebook is really good at accelerating the pace at which that is happening. Much has been written about Edgerank — the algorithm Facebook uses to decide what stories to show in people’s News feeds — and how it ends up promoting confirmation bias by only showing users stories that they are likely to agree with. Facebook knows the truth behind Clay A. Johnson’s words in The Information Diet:

Just as food companies learned that if they want to sell a lot of cheap calories, they should pack them with salt, fat, and sugar — the stuff that people crave — media companies learned that affirmation sells a lot better than information. Who wants to hear the truth when they can hear that they’re right?

What’s even more interesting about this is that Facebook is in the process of reversing a media trend that started with telegraphy. Before the introduction of the telegraph all news was local, and had a high “information-action ratio” — meaning that you could do something about what you read or heard about. But as Neil Postman points out in Amusing Ourselves to Death:

The telegraph made a three-pronged attack on typography’s definition of discourse, introducing on a large scale irrelevance, impotence, and incoherence. These demons of discourse were aroused by the fact that telegraphy gave a form of legitimacy to the idea of context-free information; that is, to the idea that the value of information need not be tied to any function it might serve in social and political decision-making and action, but may attach merely to its novelty, interest, and curiosity. […] Most of our daily news is inert, consisting of information that gives us something to talk about but cannot lead to any meaningful action.

Television and the Internet kept this trend going. All I have to do is say the word “Kardashian” and you’ll know what I mean. But Facebook — and particularly Facebook Home — is a return to “news that’s relevant”. Because it’s news about the people you have let into your life, and therefore news you can do something with (even if it’s just liking a status). Whatever your thoughts are on the privacy and sociological implications of Facebook as a service, you have to admit that it increases “information-action ratio” by (1) giving you information that’s relevant and (2) reducing the effort required to take some kind of action on that information1. That’s pretty powerful stuff.

What Facebook Home is really about

So, let’s tie all of this together. What Home allows Facebook to do is put Edgerank and people’s “social graphs”2 on steroids by giving them easy access to their identities. A Facebook-centric phone that constantly tells you what you want to hear about yourself and your friends means that you’ll find less and less use for the rest of the Internet. And that’s very, very good for Facebook since engagement is everything for an ad-based business.

Where does this leave us? I’m trying to reserve judgment about where this road that Facebook is paving will lead us. All I know is that they are doing some very smart things from a strategic business perspective. They are making news relevant again. They are shaping people’s identities (with a lot of help from Edgerank). And now they have found a way to go beyond apps and do a complete takeover of the device that most people never leave out of their sight.

Tech journalists can write about privacy and the virtues of quitting Facebook all day long. The rest of the world won’t even hear about it, because they’ll be too busy getting immersed in the lives and identities of the friends they agree with.

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1. See Like, the Post-Literate Society ↩

2. Just remember, The Social Graph is Neither ↩

I’ve long been fascinated by the links between coffee, craft, and product design. Peter Baskerville’s answer on Quora to the question How do you compete with Starbucks in the coffee industry? is another great example of that. His answer can very easily be applied to building an online product (my emphasis added):

I concluded very quickly that Starbucks was good for tourists and those folk looking for brand association, but their appeal to the quality espresso seeking locals was limited to just one curious trial. I also saw that they were in fact following the age-old successful chain formula of adequate product + brilliant marketing rather than the other way around. So they were not actually targeting my niche unique coffee/service market, which is where I believe the independents fit in.

This is so true for the current state of software development. We used to swim in a sea of adequate products that employed brilliant marketing to convince us they’re better than they really are. Now, the products and services we gravitate towards are increasingly brilliant niche products that don’t have to rely on an overdose of traditional marketing to gain traction. From Dropbox to Clear to Instapaper, people are flocking to quality products after their “one curious trial” of the do-it-all marketing-driven alternative doesn’t quite meet their needs.

Peter goes on to list 8 specific strategies that Australian coffee shops have used to beat Starbucks. With advice like “Quality above all” and “Let your customers own you”, his answer gives product designers plenty to think about.

Some of my previous posts on this topic include Coffee, design, and the nature of craft, and How to get buy-in on your design process.

In Human Intervention as a Competitive Advantage Derek Sivers makes the case that automation isn’t always the best option:

When everyone else is trying to automate everything, using a little human intervention can be a competitive advantage. The problem is when business owners see it as a cost, instead of an opportunity. Trying to minimize costs, instead of maximize income, quality, loyalty, happiness, connection, and all those other wonderful things that come from real human attention.

You can buy a fancy phone routing system, so people have to listen to 9 options, choose option 5, then listen to 6 more options, or you can hire a charming person to pick up the phone on the first ring, and make a great impression. Which one do you think will win you new fans? […]

I know what you’re thinking — how does this scale? Derek explains that in the post as well…

Kenton Kivestu defines the difference between accuracy and precision, and then discusses what it means in the context of product decisions:

There is a significant opportunity cost in consistently prioritizing precision over accuracy. Accuracy is about launching what the market needs, precision is about optimizing and delivering relentlessly on it. Unless you’ve nailed the former, material effort on the latter is going to be wasted because you’re optimizing something too far from the true north (the accurate goal) you should be pursuing.

This is an important point. Any call for data-driven design (in the quantitative, 41 shades of blue sense of the word) needs to come with a disclaimer that it’s an extremely useful approach to get closer to the middle of a target (precision), but it’s useless if you’re shooting at the wrong thing (accuracy).

(link via @ixhd)

Mitch Lasky wrote a very interesting analysis of the gaming industry’s move from packaged goods to digital goods. From EA and the Future:

In my experience, the incumbent packaged goods companies clearly see mobile, digital distribution and free-to-play models as inevitable. They know what’s coming and have known for some time. But within the senior management ranks of these companies there is still a lingering perception that digital doesn’t, in their words, “move the needle” sufficiently — meaning that the revenue generated from existing console franchises still far exceeds the revenue that can be generated, even in aggregate, on new platforms and through new business models.

Mitch goes on to show how this thinking is wrong, and then explains how being caught between the promise of new consoles and the possibilities of digital revenue puts game manufacturers in a situation where they’ll have to make some very tough strategic decisions.

(link via @hunterwalk)

Jared Spool looks at different redesign strategies in Extraordinarily Radical Redesign Strategies. Whenever time and budget allow it, I believe the “realign” strategy — what Jared calls “The Glacial-Speed Approach” — works best. This strategy relies on continuous, incremental change to reach your site goals:

The beauty of making small changes means that you never have high risk. A menu item here, a new form field there. Slowly the interface morphs, and if you make a mistake, well, you change it back.

But here’s the kicker — the reality that makes most product teams opt for a different strategy:

This type of redesign takes patience. It also takes humility, especially from those organizations who think people want to hear that they’ve made it better. Unfortunately, to most people, those proclamations sound like the web equivalent of “Our menus have changed so please listen carefully.”

To pull this off, the team needs a solid vision of where the design should eventually go. Then, one small change at a time, they start. Make the change and watch what happens, proceeding slowly to the next. The team will know it’s succeeded when they hear a user insist that a new addition has been in the design all along.

Patience isn’t a word most people would use to describe their leadership teams when it comes to site redesigns. But the reality is that most other strategies involve much higher risks than the internal frustration of waiting a few extra months using the realignment approach. Risks like losing the majority of your customer base to a competitor (as Digg found out the hard way).

Read Jared’s article for a good overview of the pros and cons of different redesign strategies.

In The Guardian Tom Meltzer asks, Are our household appliances getting too complicated? Despite violating Betteridge’s law of headlines he makes some good points:

“The innovation is obviously being driven by manufacturers’ desire to add value and to differentiate themselves,” says analyst Neil Mason, head of retail research at market research company Mintel. “But from a consumer’s point of view, what they want is convenience and simplicity. When you run into trouble is when you add all these extra functions and consumers just get perplexed as to how to actually use them.”

He cites some classic examples of technology-driven innovation — asking “What more can we do with this technology?” as opposed to “What goals do our customers want to accomplish with our product?”

A Readlist of all the articles referenced in this post is available here. Readlists allow you to send all the articles to your Kindle, read them on your iOS device, or download it as an e-book.

Despite the overly alarmist title, Andrew Leonard’s How Netflix is turning viewers into puppets1 is a fascinating article on how Netflix uses Big Data in their programming decisions:

“House of Cards” is one of the first major test cases of this Big Data-driven creative strategy. For almost a year, Netflix executives have told us that their detailed knowledge of Netflix subscriber viewing preferences clinched their decision to license a remake of the popular and critically well regarded 1990 BBC miniseries. Netflix’s data indicated that the same subscribers who loved the original BBC production also gobbled down movies starring Kevin Spacey or directed by David Fincher. Therefore, concluded Netflix executives, a remake of the BBC drama with Spacey and Fincher attached was a no-brainer, to the point that the company committed $100 million for two 13-episode seasons.

The article also asks what this approach means for the creative process, something I’ve written about before in The unnecessary fear of digital perfection, so I won’t rehash that argument here.

What’s interesting to me about the rise in Big Data approaches to decision-making is the high levels of inaccuracy inherent to the analysis process. Of course, this is something we don’t hear about often, but Nassim N. Taleb recently wrote a great opinion piece about it for Wired called Beware the Big Errors of ‘Big Data’, in which he states:

Big-data researchers have the option to stop doing their research once they have the right result. In options language: The researcher gets the “upside” and truth gets the “downside.” It makes him antifragile, that is, capable of benefiting from complexity and uncertainty — and at the expense of others.

But beyond that, big data means anyone can find fake statistical relationships, since the spurious rises to the surface. This is because in large data sets, large deviations are vastly more attributable to variance (or noise) than to information (or signal). It’s a property of sampling: In real life there is no cherry-picking, but on the researcher’s computer, there is. Large deviations are likely to be bogus.

He gets into more detail on the statistical problems with Big Data in the article, and his book Antifragile looks really interesting too.

Since I haven’t written about Big Data before, I also want to reference a few articles on the topic that I enjoyed. Sean Madden gives some interesting real world examples in How Companies Like Amazon Use Big Data To Make You Love Them2. But over on the skeptical side, Stephen Few argues in Big Data, Big Deal that “interest in big data today is a direct result of vendor marketing; it didn’t emerge naturally from the needs of users.” He also makes the point that data has always been big, and that by focusing on the “bigness” of it, we’re missing the point:

A little more and a little faster have always been on our wish list. While information technology has struggled to catch up, mostly by pumping itself up with steroids, it has lost sight of the objective: to better understand the world—at least one’s little part of it (e.g., one’s business)—so we can make it better. Our current fascination with big data has us looking for better steroids to increase our brawn rather than better skills to develop our brains. In the world of analytics, brawn will only get us so far; it is better thinking that will open the door to greater insight.

Alan Mitchell makes a similar point in Big Data, Big Dead End, a case for what he calls Small Data:

But if we look at the really big value gap faced by society nowadays, it’s not the ability to crunch together vast amounts of data, but quite the opposite. It’s the challenge of information logistics: of how to get exactly the right information to, and from, the right people in the right formats at the right time. This is about Very Small Data: discarding or leaving aside the 99.99% of information I don’t need right now so that I can use the 0.01% of information that I do need as quickly and efficiently as possible.

What I think we should take from all of this is that our ability to collect vast amounts of data comes with enormous predictive and analytical upside. But we’d be foolish to think that it makes decision-making easier. Because Big Data does not take away the biggest challenge of data analysis: figuring how to turn data into information, and information into knowledge. In fact, Big Data makes this harder. To quote Nassim again:

I am not saying here that there is no information in big data. There is plenty of information. The problem — the central issue — is that the needle comes in an increasingly larger haystack.

In other words: proceed with caution.

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1. Link via @mobivangelist ↩

2. It’s interesting that the phrasing of both this headline and the Netflix one implies that companies are using Big Data to persuade us to do things against our will. But I can’t figure out if that’s a real fear, or just clever linkbait. ↩